#!/usr/bin/env python
# Copyright (c) Alibaba, Inc. and its affiliates.

import argparse
import datetime
import math
import os
import subprocess
import sys
sys.path.insert(0, '/swift')
import tempfile
import time
import unittest
from fnmatch import fnmatch
from pathlib import Path
from unittest import TextTestResult

import pandas
# NOTICE: Tensorflow 1.15 seems not so compatible with pytorch.
#         A segmentation fault may be raise by pytorch cpp library
#         if 'import tensorflow' in front of 'import torch'.
#         Putting a 'import torch' here can bypass this incompatibility.
import torch
import yaml
from model_tag import ModelTag, commit_model_ut_result
from test_utils import get_case_model_info

from swift.utils.logger import get_logger

logger = get_logger()


def test_cases_result_to_df(result_list):
    table_header = [
        'Name', 'Result', 'Info', 'Start time', 'Stop time',
        'Time cost(seconds)'
    ]
    df = pandas.DataFrame(
        result_list, columns=table_header).sort_values(
            by=['Start time'], ascending=True)
    return df


def statistics_test_result(df):
    total_cases = df.shape[0]
    # yapf: disable
    success_cases = df.loc[df['Result'] == 'Success'].shape[0]
    error_cases = df.loc[df['Result'] == 'Error'].shape[0]
    failures_cases = df.loc[df['Result'] == 'Failures'].shape[0]
    expected_failure_cases = df.loc[df['Result'] == 'ExpectedFailures'].shape[0]
    unexpected_success_cases = df.loc[df['Result'] == 'UnexpectedSuccesses'].shape[0]
    skipped_cases = df.loc[df['Result'] == 'Skipped'].shape[0]
    # yapf: enable

    if failures_cases > 0 or \
       error_cases > 0 or \
       unexpected_success_cases > 0:
        final_result = 'FAILED'
    else:
        final_result = 'SUCCESS'
    result_msg = '%s (Runs=%s,success=%s,failures=%s,errors=%s,\
    skipped=%s,expected failures=%s,unexpected successes=%s)' % (
        final_result, total_cases, success_cases, failures_cases, error_cases,
        skipped_cases, expected_failure_cases, unexpected_success_cases)

    model_cases = get_case_model_info()
    for model_name, case_info in model_cases.items():
        cases = df.loc[df['Name'].str.contains('|'.join(list(case_info)))]
        results = cases['Result']
        result = None
        if any(results == 'Error') or any(results == 'Failures') or any(
                results == 'UnexpectedSuccesses'):
            result = ModelTag.MODEL_FAIL
        elif any(results == 'Success'):
            result = ModelTag.MODEL_PASS
        elif all(results == 'Skipped'):
            result = ModelTag.MODEL_SKIP
        else:
            print(f'invalid results for {model_name} \n{result}')

        if result is not None:
            commit_model_ut_result(model_name, result)
    print('Testing result summary.')
    print(result_msg)
    if final_result == 'FAILED':
        sys.exit(1)


def gather_test_suites_in_files(test_dir, case_file_list, list_tests):
    test_suite = unittest.TestSuite()
    for case in case_file_list:
        test_case = unittest.defaultTestLoader.discover(
            start_dir=test_dir, pattern=case)
        test_suite.addTest(test_case)
        if hasattr(test_case, '__iter__'):
            for subcase in test_case:
                if list_tests:
                    print(subcase)
        else:
            if list_tests:
                print(test_case)
    return test_suite


def gather_test_suites_files(test_dir, pattern):
    case_file_list = []
    for dirpath, dirnames, filenames in os.walk(test_dir):
        for file in filenames:
            if fnmatch(file, pattern):
                case_file_list.append(file)

    return case_file_list


def collect_test_results(case_results):
    result_list = [
    ]  # each item is Case, Result, Start time, Stop time, Time cost
    for case_result in case_results.successes:
        result_list.append(
            (case_result.test_full_name, 'Success', '', case_result.start_time,
             case_result.stop_time, case_result.time_cost))
    for case_result in case_results.errors:
        result_list.append(
            (case_result[0].test_full_name, 'Error', case_result[1],
             case_result[0].start_time, case_result[0].stop_time,
             case_result[0].time_cost))
    for case_result in case_results.skipped:
        result_list.append(
            (case_result[0].test_full_name, 'Skipped', case_result[1],
             case_result[0].start_time, case_result[0].stop_time,
             case_result[0].time_cost))
    for case_result in case_results.expectedFailures:
        result_list.append(
            (case_result[0].test_full_name, 'ExpectedFailures', case_result[1],
             case_result[0].start_time, case_result[0].stop_time,
             case_result[0].time_cost))
    for case_result in case_results.failures:
        result_list.append(
            (case_result[0].test_full_name, 'Failures', case_result[1],
             case_result[0].start_time, case_result[0].stop_time,
             case_result[0].time_cost))
    for case_result in case_results.unexpectedSuccesses:
        result_list.append((case_result.test_full_name, 'UnexpectedSuccesses',
                            '', case_result.start_time, case_result.stop_time,
                            case_result.time_cost))
    return result_list


def run_command_with_popen(cmd):
    with subprocess.Popen(
            cmd,
            stdout=subprocess.PIPE,
            stderr=subprocess.STDOUT,
            bufsize=1,
            encoding='utf8') as sub_process:
        for line in iter(sub_process.stdout.readline, ''):
            sys.stdout.write(line)


def async_run_command_with_popen(cmd, device_id):
    logger.info('Worker id: %s args: %s' % (device_id, cmd))
    env = os.environ.copy()
    env['CUDA_VISIBLE_DEVICES'] = '%s' % device_id
    sub_process = subprocess.Popen(
        cmd,
        stdout=subprocess.PIPE,
        stderr=subprocess.STDOUT,
        bufsize=1,
        universal_newlines=True,
        env=env,
        encoding='utf8')
    return sub_process


def save_test_result(df, args):
    if args.result_dir is not None:
        file_name = str(int(datetime.datetime.now().timestamp() * 1000))
        os.umask(0)
        Path(args.result_dir).mkdir(mode=0o777, parents=True, exist_ok=True)
        Path(os.path.join(args.result_dir, file_name)).touch(
            mode=0o666, exist_ok=True)
        df.to_pickle(os.path.join(args.result_dir, file_name))


def run_command(cmd):
    logger.info('Running command: %s' % ' '.join(cmd))
    response = subprocess.run(
        cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
    try:
        response.check_returncode()
        logger.info(response.stdout.decode('utf8'))
    except subprocess.CalledProcessError as error:
        logger.error(
            'stdout: %s, stderr: %s' %
            (response.stdout.decode('utf8'), error.stderr.decode('utf8')))


def install_packages(pkgs):
    if pkgs is None:
        return
    cmd = [sys.executable, '-m', 'pip', 'install']
    for pkg in pkgs:
        cmd.append(pkg)

    run_command(cmd)


def install_requirements(requirements):
    for req in requirements:
        cmd = [
            sys.executable, '-m', 'pip', 'install', '-r',
            'requirements/%s' % req, '-f',
            'https://modelscope.oss-cn-beijing.aliyuncs.com/releases/repo.html'
        ]
        run_command(cmd)


def wait_for_free_worker(workers):
    while True:
        for idx, worker in enumerate(workers):
            if worker is None:
                logger.info('return free worker: %s' % (idx))
                return idx
            if worker.poll() is None:  # running, get output
                for line in iter(worker.stdout.readline, ''):
                    if line != '':
                        sys.stdout.write(line)
                    else:
                        break
            else:  # worker process completed.
                logger.info('Process end: %s' % (idx))
                workers[idx] = None
                return idx
        time.sleep(0.001)


def wait_for_workers(workers):
    while True:
        for idx, worker in enumerate(workers):
            if worker is None:
                continue
            # check worker is completed.
            if worker.poll() is None:
                for line in iter(worker.stdout.readline, ''):
                    if line != '':
                        sys.stdout.write(line)
                    else:
                        break
            else:
                logger.info('Process idx: %s end!' % (idx))
                workers[idx] = None

        is_all_completed = True
        for idx, worker in enumerate(workers):
            if worker is not None:
                is_all_completed = False
                break

        if is_all_completed:
            logger.info('All sub process is completed!')
            break
        time.sleep(0.001)


def parallel_run_case_in_env(env_name, env, test_suite_env_map, isolated_cases,
                             result_dir, parallel):
    logger.info('Running case in env: %s' % env_name)
    # install requirements and deps # run_config['envs'][env]
    if 'requirements' in env:
        install_requirements(env['requirements'])
    if 'dependencies' in env:
        install_packages(env['dependencies'])
    # case worker processes
    worker_processes = [None] * parallel
    for test_suite_file in isolated_cases:  # run case in subprocess
        if test_suite_file in test_suite_env_map and test_suite_env_map[
                test_suite_file] == env_name:
            cmd = [
                'python',
                'tests/run.py',
                '--pattern',
                test_suite_file,
                '--result_dir',
                result_dir,
            ]
            worker_idx = wait_for_free_worker(worker_processes)
            worker_process = async_run_command_with_popen(cmd, worker_idx)
            os.set_blocking(worker_process.stdout.fileno(), False)
            worker_processes[worker_idx] = worker_process
        else:
            pass  # case not in run list.

    # run remain cases in a process.
    remain_suite_files = []
    for k, v in test_suite_env_map.items():
        if k not in isolated_cases and v == env_name:
            remain_suite_files.append(k)
    if len(remain_suite_files) == 0:
        wait_for_workers(worker_processes)
        return
    # roughly split case in parallel
    part_count = math.ceil(len(remain_suite_files) / parallel)
    suites_chunks = [
        remain_suite_files[x:x + part_count]
        for x in range(0, len(remain_suite_files), part_count)
    ]
    for suites_chunk in suites_chunks:
        worker_idx = wait_for_free_worker(worker_processes)
        cmd = [
            'python', 'tests/run.py', '--result_dir', result_dir, '--suites'
        ]
        for suite in suites_chunk:
            cmd.append(suite)
        worker_process = async_run_command_with_popen(cmd, worker_idx)
        os.set_blocking(worker_process.stdout.fileno(), False)
        worker_processes[worker_idx] = worker_process

    wait_for_workers(worker_processes)


def run_case_in_env(env_name, env, test_suite_env_map, isolated_cases,
                    result_dir):
    # install requirements and deps # run_config['envs'][env]
    if 'requirements' in env:
        install_requirements(env['requirements'])
    if 'dependencies' in env:
        install_packages(env['dependencies'])

    for test_suite_file in isolated_cases:  # run case in subprocess
        if test_suite_file in test_suite_env_map and test_suite_env_map[
                test_suite_file] == env_name:
            cmd = [
                'python',
                'tests/run.py',
                '--pattern',
                test_suite_file,
                '--result_dir',
                result_dir,
            ]
            run_command_with_popen(cmd)
        else:
            pass  # case not in run list.

    # run remain cases in a process.
    remain_suite_files = []
    for k, v in test_suite_env_map.items():
        if k not in isolated_cases and v == env_name:
            remain_suite_files.append(k)
    if len(remain_suite_files) == 0:
        return
    cmd = ['python', 'tests/run.py', '--result_dir', result_dir, '--suites']
    for suite in remain_suite_files:
        cmd.append(suite)
    run_command_with_popen(cmd)


def run_non_parallelizable_test_suites(suites, result_dir):
    cmd = ['python', 'tests/run.py', '--result_dir', result_dir, '--suites']
    for suite in suites:
        cmd.append(suite)
    run_command_with_popen(cmd)


# Selected cases:
def get_selected_cases():
    cmd = ['python', '-u', 'tests/run_analysis.py']
    selected_cases = []
    with subprocess.Popen(
            cmd,
            stdout=subprocess.PIPE,
            stderr=subprocess.STDOUT,
            bufsize=1,
            encoding='utf8') as sub_process:
        for line in iter(sub_process.stdout.readline, ''):
            sys.stdout.write(line)
            if line.startswith('Selected cases:'):
                line = line.replace('Selected cases:', '').strip()
                selected_cases = line.split(',')
        sub_process.wait()
        if sub_process.returncode != 0:
            msg = 'Run analysis exception, returncode: %s!' % sub_process.returncode
            logger.error(msg)
            raise Exception(msg)
    return selected_cases


def run_in_subprocess(args):
    # only case args.isolated_cases run in subprocess, all other run in a subprocess
    if not args.no_diff:  # run based on git diff
        try:
            test_suite_files = get_selected_cases()
            logger.info('Tests suite to run: ')
            for f in test_suite_files:
                logger.info(f)
        except Exception:
            logger.error(
                'Get test suite based diff exception!, will run all cases.')
            test_suite_files = gather_test_suites_files(
                os.path.abspath(args.test_dir), args.pattern)
        if len(test_suite_files) == 0:
            logger.error('Get no test suite based on diff, run all the cases.')
            test_suite_files = gather_test_suites_files(
                os.path.abspath(args.test_dir), args.pattern)
    else:
        test_suite_files = gather_test_suites_files(
            os.path.abspath(args.test_dir), args.pattern)

    non_parallelizable_suites = []
    test_suite_files = [
        x for x in test_suite_files if x not in non_parallelizable_suites
    ]

    run_config = None
    isolated_cases = []
    test_suite_env_map = {}
    # put all the case in default env.
    for test_suite_file in test_suite_files:
        test_suite_env_map[test_suite_file] = 'default'

    if args.run_config is not None and Path(args.run_config).exists():
        with open(args.run_config, encoding='utf-8') as f:
            run_config = yaml.safe_load(f)
        if 'isolated' in run_config:
            isolated_cases = run_config['isolated']

        if 'envs' in run_config:
            for env in run_config['envs']:
                if env != 'default':
                    for test_suite in run_config['envs'][env]['tests']:
                        if test_suite in test_suite_env_map:
                            test_suite_env_map[test_suite] = env

    if args.subprocess:  # run all case in subprocess
        isolated_cases = test_suite_files

    with tempfile.TemporaryDirectory() as temp_result_dir:
        # first run cases that nonparallelizable
        run_non_parallelizable_test_suites(non_parallelizable_suites,
                                           temp_result_dir)

        # run case parallel in envs
        for env in set(test_suite_env_map.values()):
            parallel_run_case_in_env(env, run_config['envs'][env],
                                     test_suite_env_map, isolated_cases,
                                     temp_result_dir, args.parallel)

        result_dfs = []
        result_path = Path(temp_result_dir)
        for result in result_path.iterdir():
            if Path.is_file(result):
                df = pandas.read_pickle(result)
                result_dfs.append(df)
        result_pd = pandas.concat(
            result_dfs)  # merge result of every test suite.
        print_table_result(result_pd)
        print_abnormal_case_info(result_pd)
        statistics_test_result(result_pd)


def get_object_full_name(obj):
    klass = obj.__class__
    module = klass.__module__
    if module == 'builtins':
        return klass.__qualname__
    return module + '.' + klass.__qualname__


class TimeCostTextTestResult(TextTestResult):
    """Record test case time used!"""

    def __init__(self, stream, descriptions, verbosity):
        self.successes = []
        super(TimeCostTextTestResult,
                     self).__init__(stream, descriptions, verbosity)

    def startTest(self, test):
        test.start_time = datetime.datetime.now()
        test.test_full_name = get_object_full_name(
            test) + '.' + test._testMethodName
        self.stream.writeln('Test case:  %s start at: %s' %
                            (test.test_full_name, test.start_time))

        return super(TimeCostTextTestResult, self).startTest(test)

    def stopTest(self, test):
        TextTestResult.stopTest(self, test)
        test.stop_time = datetime.datetime.now()
        test.time_cost = (test.stop_time - test.start_time).total_seconds()
        self.stream.writeln(
            'Test case: %s stop at: %s, cost time: %s(seconds)' %
            (test.test_full_name, test.stop_time, test.time_cost))
        if torch.cuda.is_available(
        ) and test.time_cost > 5.0:  # print nvidia-smi
            cmd = ['nvidia-smi']
            run_command_with_popen(cmd)
        super(TimeCostTextTestResult, self).stopTest(test)

    def addSuccess(self, test):
        self.successes.append(test)
        super(TextTestResult, self).addSuccess(test)


class TimeCostTextTestRunner(unittest.runner.TextTestRunner):
    resultclass = TimeCostTextTestResult

    def run(self, test):
        return super(TimeCostTextTestRunner, self).run(test)

    def _makeResult(self):
        result = super(TimeCostTextTestRunner, self)._makeResult()
        return result


def gather_test_cases(test_dir, pattern, list_tests):
    case_list = []
    for dirpath, dirnames, filenames in os.walk(test_dir):
        for file in filenames:
            if fnmatch(file, pattern):
                case_list.append(file)

    test_suite = unittest.TestSuite()

    for case in case_list:
        test_case = unittest.defaultTestLoader.discover(
            start_dir=test_dir, pattern=case)
        test_suite.addTest(test_case)
        if hasattr(test_case, '__iter__'):
            for subcase in test_case:
                if list_tests:
                    print(subcase)
        else:
            if list_tests:
                print(test_case)
    return test_suite


def print_abnormal_case_info(df):
    df = df.loc[(df['Result'] == 'Error') | (df['Result'] == 'Failures')]
    for _, row in df.iterrows():
        print('Case %s run result: %s, msg:\n%s' %
              (row['Name'], row['Result'], row['Info']))


def print_table_result(df):
    df = df.loc[df['Result'] != 'Skipped']
    df = df.drop('Info', axis=1)
    formatters = {
        'Name': '{{:<{}s}}'.format(df['Name'].str.len().max()).format,
        'Result': '{{:<{}s}}'.format(df['Result'].str.len().max()).format,
    }
    with pandas.option_context('display.max_rows', None, 'display.max_columns',
                               None, 'display.width', None):
        print(df.to_string(justify='left', formatters=formatters, index=False))


def main(args):
    runner = TimeCostTextTestRunner()
    if args.suites is not None and len(args.suites) > 0:
        logger.info('Running: %s' % ' '.join(args.suites))
        test_suite = gather_test_suites_in_files(args.test_dir, args.suites,
                                                 args.list_tests)
    else:
        test_suite = gather_test_cases(
            os.path.abspath(args.test_dir), args.pattern, args.list_tests)
    if not args.list_tests:
        result = runner.run(test_suite)
        logger.info('Running case completed, pid: %s, suites: %s' %
                    (os.getpid(), args.suites))
        result = collect_test_results(result)
        df = test_cases_result_to_df(result)
        if args.result_dir is not None:
            save_test_result(df, args)
        else:
            print_table_result(df)
            print_abnormal_case_info(df)
            statistics_test_result(df)


if __name__ == '__main__':
    parser = argparse.ArgumentParser('test runner')
    parser.add_argument(
        '--list_tests', action='store_true', help='list all tests')
    parser.add_argument(
        '--pattern', default='test_*.py', help='test file pattern')
    parser.add_argument(
        '--test_dir', default='tests', help='directory to be tested')
    parser.add_argument(
        '--level', default=0, type=int, help='2 -- all, 1 -- p1, 0 -- p0')
    parser.add_argument(
        '--profile', action='store_true', help='enable profiling')
    parser.add_argument(
        '--run_config',
        default=None,
        help='specified case run config file(yaml file)')
    parser.add_argument(
        '--subprocess',
        action='store_true',
        help='run all test suite in subprocess')
    parser.add_argument(
        '--result_dir',
        default=None,
        help='Save result to directory, internal use only')
    parser.add_argument(
        '--parallel',
        default=1,
        type=int,
        help='Set case parallels, default single process, set with gpu number.'
    )
    parser.add_argument(
        '--no-diff',
        action='store_true',
        help=
        'Default running case based on git diff(with master), disable with --no-diff)'
    )
    parser.add_argument(
        '--suites',
        nargs='*',
        help='Run specified test suites(test suite files list split by space)')
    args = parser.parse_args()
    print(args)
    if args.run_config is not None or args.subprocess:
        run_in_subprocess(args)
    else:
        main(args)
